Uma Abordagem para Detecção Automática de Planos em Modelos Digitais de Afloramentos Baseada em PCA

Abstract

The use of LIDAR (Light Detection and Ranging) systems for gathering spatial data has been extensively used in geological studies. This type of digital remote sensing delivers high resolution and accuracy, resulting in 3D digital models which allow a more detailed and quantitative analysis of heterogeneous structures, as outcrops. One of the studies is based on analysis of the forming rocks geometry. The orientation of a slope plane is an indication for the overall undestanding of the structure. This work proposes a new method to automatically compute and detect all possible planes in a point cloud, based on Principal Component Analysis (PCA) technique. A software tool was constructed to implement the digital model visualization and compute the best planes. A study was conducted to compare and validate the results of the method and the field data collected.